Fundamentals of Predictive Text Mining Hardback
Part of the Texts in Computer Science series
This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics.
Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies.
This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining social media, errors and pitfalls in big data evaluation, Twitter sentiment analysis, and dependency parsing discussion.
The fully updated content also features in-depth discussions on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation.
Features: includes chapter summaries and exercises; explores the application of each method; provides several case studies; contains links to free text-mining software.
- Format: Hardback
- Pages: 239 pages, 22 Tables, black and white; 115 Illustrations, black and white; XIII, 239 p. 115 illus.
- Publisher: Springer London Ltd
- Publication Date: 14/09/2015
- Category: Public administration
- ISBN: 9781447167495
- Paperback / softback from £40.79
- PDF from £42.49
- Hardback from £37.39